NSDC Data Science Flashcards – Probability #4 – Expected Value

This NSDC Data Science Flashcards series will teach you about probability, including random variables, probability density functions, cumulative distribution functions, and expected values. This installment of the NSDC Data Science Flashcards series was created and recorded by Stephanie Guo. You can find these videos on the NEBDHub Youtube channel.

Hello everyone, my name is Stephanie and I am the Program Manager for the National Student Data Corps. Welcome to the NSDC Data Science Flashcard Video Series. This series will break down data science topics in simple terms that you can leverage throughout your data science journey. Today, we’ll be talking about probability.

Lastly, let’s touch upon the Expected Value. It represents the average or mean value of a random variable.

For discrete random variables, we calculate it using the sum of all possible values multiplied by their probabilities. For continuous random variables, it’s the integral of the product of the variable and its probability density function.

The expected value gives us a sense of the ‘center’ of a distribution, a crucial concept in probability and statistics. To sum it up, random variables and their functions form the backbone of statistics, guiding us in analyzing data and making informed decisions. Stay tuned for more detailed explorations in our upcoming segments!

Please follow along with the rest of the NSDC Data Science Flashcard series to learn more about math and probability.